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Task: Find-Replace Undesired Translation with Desired One

The next "sprint" is to build a module that finds and replaces undesired translations with desired ones if a given glossary term occurs in any word form in the Russian original. English verbs in the third person singular and nouns in the plural and Saxon genitive ending in "-s" are going to have to be accommodated, as are Russian declensions and conjugations. Actually, this "if" condition may be unnecessary after all, and is more of a quality control mechanism. Let's keep it for now, time and resource permitting. Full steam ahead!

I am a Python neural machine translation (NMT) consultant who
specializes in Russian, Polish, and Carpatho-Rusyn (Lemko). I would be
glad to help you. Send me an email or call me here:
pgleasonjr+office@gmail.com, +1-405-TRANSL8

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In what was a small step for neural machine translation (NMT) and hopefully a giant leap for Lemko natural language processing (NLP), I have processed the first sentence ever in the minority language using using next-generation, zero-shot artificial intelligence (AI) machine translation.Other methods thus far have required treating Lemko as a dialect of neighboring, state-sponsored official languages.The first sentence was "Яка політыка?" translated as "What politics?" The material for this project has been generously made available by an NGO specializing in preserving Lemko language and culture.I used Google Tensorflow CPU stable build tf-1.2 on a Lenovo M30 laptop running Ubuntu 16.04. I am considering a cloud computing solution for future development work.

[UPDATE 1530 CET 2017/05/15: The report in question has now been published by Adzuna (link) ]

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